Open Access
Review Article, Biomed Biopharm Res., 2023; 20(1):126-135
doi: 10.19277/bbr.20.1.312; PDF version [+]; Portuguese html [PT] 

 

 

 A review of the study of environmental modeling tools to understand the real impact of cosmetic products on environmental safety

Caroline Inácio Bianchi and Patrícia Maria Berardo Gonçalves Maia Campos ✉️

Faculdade de Ciências Farmacêuticas de Ribeirão Preto – Universidade de São Paulo, Avenida do Café, S/N, Ribeirão Preto - SP, 14040-903l

 

Abstract

In contrast to human health risk assessment, there are no definitive guidelines for environmental risk assessment of cosmetic products. The objective of this study was to perform an in-depth analysis of ten modeling environmental tools and to establish the best rationale to assess the impact on environmental safety considering the recent global pandemic scenario and the evolution of the consumer mindset. A literature analysis was performed for the ten modeling environmental tools, and when possible, each was downloaded for comparison. Chesar was the tool that proved to be the easiest to enter data, and it has the more straightforward and direct application steps; thus, it was chosen for the initial assessment of ingredients that demonstrate potential environmental hazards. For high-level tools, it was not possible to establish a comparison for choice, as the models are private and have little data in the literature. Even so, for a more detailed assessment after the first initial assessment via Chesar, iSTREEM could be used. This study delivers important knowledge about the modeling tools and how to establish a rationale for environmental risk assessment.

Keywords: Environmental risk assessment, cosmetic products, environmental impact, formulation

To Cite: Bianchi, C. I. &. Maia Campos, P. M. B. G. (2023)   A review of the study of environmental modeling tools to understand the real impact of cosmetic products on environmental safety. Biomedical and Biopharmaceutical Research, 20(1), 126-135..

Correspondence to: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received 18/04/2023; Accepted 12/07/2023

 

Introduction

From the twentieth century, the period in which cosmetic products gained market share, to the current context, a natural evolution in consumer mentality could be observed. Over the years, the concern becomes not only with the cosmetic efficacy of the product, but also with the human and environmental safety of the products purchased, and the cosmetic industries need to be aware of these and other new needs (1).

To understand the evolution of the mindset over the years, as well as the current mentality, it is necessary to understand the context in which the consumer is inserted because, although consumption is habitual, it is also contextual and governed by the characteristics of the period.

There are four main contexts that interfere in the change of consumption habits: (1) change in the social context; (2) technological; (3) rules and regulations and, (4) natural disasters such as earthquakes, hurricanes, and global pandemics such as the Covid-19 pandemic we have experienced. All these contexts can significantly interfere with both consumption and production and the supply chain (2), and, specifically discussing the pandemic caused by the Coronavirus SARS-CoV-2, impacts and changes in consumption habits have been observed since March 2020.

According to the World Health Organization, one of the actions that helps prevent the disease is frequent and thorough hand hygiene, with soap and water or the use of hand sanitizers (3). The contagious nature of the new virus has raised awareness about the importance of personal hygiene, which may explain, for example, the 80% increase in spending on personal hygiene products in the same period in Australia (4) and understanding how hand washing behavior can suggest health knowledge (5), helping to prevent contagious diseases. Corroborating this fact, a recent Euromonitor survey (2021) indicates a growth in the frequency of liquid soap use across different continents and points out how the consumer today is "obsessed" with safety (6).

In addition to the high demand for personal hygiene products such as soaps, the opportunity for other hand products has emerged, especially those that offer repairing or healing benefits (7), as excessive use of hygiene and cleaning products can damage the skin barrier function, increasing transepidermal water loss (TEWL), favoring the appearance of skin irritations (8).

Thus, the emphasis on hand care during the pandemic period led to an increase in the use of liquid soaps and hand moisturizers and, consequently, an increase in consumer and environmental exposure to the ingredients of these formulations, which can directly impact human and environmental safety. Given this scenario, it is of great importance to conduct studies aimed at meeting the new needs of consumers, as well as ensuring human and environmental safety in the face of new exposure.

The theoretical evaluation of ingredients for human and environmental safety and the choice of ingredients for cosmetic formulations begins with the study of the toxicological profile (hazard), analyzing all possible toxicological results for each ingredient used in the formulation. The mode of use of the product, the exposure, and the target audience are then considered. After that, risk assessment is required (9), starting from hazard identification, dose-response assessment, exposure assessment, and risk characterization calculating the margin of safety and quantitative comparisons. Robust guidelines exist for human safety risk assessment, (9,10). However, there are no well-defined guidelines for environmental risk assessment.

Due to differences in socioeconomic and environmental factors, including product use, wastewater treatment infrastructure, and dilution in receiving waters, large spatial variations in exposure to these “down-the-drain” wastewater chemicals are expected between countries and regions, and even within the same basin (11). Therefore, it is extremely challenging to map and perform an environmental risk assessment for all scenarios.

Alternatively, to understand the potential environmental hazards of cosmetic product ingredients, modeling approaches can be used to provide predicted environmental concentrations (PECs) of ingredients and provide a means to perform an environmental risk assessment by comparing PECs with toxicity thresholds for Predicted No-Effect Concentrations (PNECs)

In the cosmetic scenario, formulations are known to be continuously introduced into aquatic systems and, unlike pharmaceutical products, for example, cosmetic products present ecological risks of greater perseverance due to their continuous use throughout life and that they are not metabolized prior to exposure.

According to the last Society of Environmental Toxicology and Chemistry (SETAC) workshop in 2016, there are ten environmental modeling tools that can perform an environmental risk assessment: E-FAST (USA), EUSES (EU), Chesar (EU), CRAM (Canada), HydroROUT CFM (St. Lawrence R.), GREAT-ER (Europe), STREAM-EU (Europe), ScenAT (World), PhATE™ (USA), iSTREEM® (USA + Ontario).

In this context, the aim of this study was to perform an in-depth analysis of these ten environmental modeling tools and establish the best rationale for assessing the impact on environmental safety considering the recent global scenario and contributing to the development of safer cosmetics for humans and the environment.

The ten methodologies were studied through the literature, using articles, tool manuals and environmental safety assessment guides, such that each type of model could be understood. After that, some modeling tools could be downloaded to compare and analyze against the ECHA (European Chemical Agency) Guidance.

Finally, it was possible to choose one screening model for initial risk assessment and a high-level model for in-depth risk assessment.

This study had an innovative proposal, as it presented the study and comparison of ten environmental modeling tools that can assist in the environmental risk assessment required by the European Directive and the new mindset of cosmetic product consumers.

In this context, this study brings an important contribution by proposing a complete rationale for environmental risk assessment, considering the study of computational models and contributing to the development of safer cosmetics for humans and the environment.

Materials and methods

Based on the literature review, modeling tools were studied and divided into two groups:

- Screening models: conservative assessment that standardizes the data.
- High-level models: detailed assessment that requires more information about the location to be evaluated.

With the studies of ECHA literature, it was possible to understand the four steps needed to make the environmental risk assessment: Input, Estimation of substance release, Environmental distribution and Risk characterization, in addition to other parameters, as indicated in Figure 1.

Figure 1 - Comparison of screening models under the evaluation parameters.
bbr.20.1.312.Fig1

 

Whether the tools follow the steps of ECHA on environmental risk assessment for chemicals was analyzed as a parameter.

The downloads could be made for the screening models and all the necessary inputs and parameters considered for each were tabulated for comparison.

The study of the high-tier models was based on literature, as they are private models.

Results and discussion

The ten environmental modeling tools studied follow the European Chemicals Agency Guidance on information requirements and chemical safety assessment (12): environmental exposure assessment is initially based on the evaluation of information on the relevant properties of the substance (physicochemical properties, fate and (eco)toxicological), subsequently on hazard assessment and use mapping.

At a minimum, vapor pressure, water solubility, molecular weight, octanol-water partition coefficient, melting point, and impact of biodegradability on the fate of the substance in the environment are the information necessary for the estimation of environmental exposure.

For the EUSES, Chesar and E-FAST screening models, the four steps for environmental risk assessment could be analyzed in detail:

1. Input data: inclusion in the tools of data identifying the analyte (e.g., molecular weight, partition coefficient, etc.):

In addition to the minimum data reported above, E-FAST requires the removal of effluent treatment for each substance. These data are not easy to find and usually require other tools to obtain them, which makes E-FAST the complex model at this step.

EUSES does not require as complex data as E-FAST, but it requires a great deal of information to run.

On the other hand, in Chesar (an evolution tool of EUSES), all the data may be entered through IUCLID (International Uniform ChemicaL Information Database - ECHA database), making it the best tool for this step.

2. Estimated release of the substance: considers the amount of use and the exposed population:

EUSES was found to be the most complex tool in this step because while the other modeling tools need only the annual production volume, it needs other data to make an estimate, such as tonnage and chemical analysis.

E-FAST uses the 2003 US population, and this information was considered out-of-date. Thus, Chesar once again was the best model at this stage.

3. Environmental distribution: considers the location where the substance is disposed:

In addition to effluent removal treatment for each substance, E-FAST requires river flow and is another complex data compared to EUSES and Chesar.

4. Risk characterization: Based on the data reported in Steps 1, 2 and 3, the tools compare actual exposure with ideal exposure:

The risk characterization is different for these tools. While EUSES and Chesar make an environmental risk assessment based on the calculation of the CAP/CENP value, E-FAST uses a program that the assessor needs to enter the days of the period, and the program will determine how often the stream receiving the concentration will exceed the level of concern (LDC).

For the high-level assessment tools (CRAM (Canada), HydroROUT CFM (St. Lawrence R.), GREAT-ER (Europe), STREAM-EU (Europe), ScenAT (World), PhATE™ (USA), iSTREEM® (USA + Ontario)), there are often common assumptions shared and similar key modeling mechanisms. But while in screening models removal and dilution rates are fixed and the worst case scenario is considered, it is possible to modify such factors in the high-level models (13).

A detailed assessment covering the four steps of environmental risk assessment could not be performed as the only one available for download and testing was iSTREEM®.

iSTREEM® is a free tool, a web-based GIS model that estimates the concentration of a chemical going down the drain and the residual levels that subsequently enter the aquatic environment. This publicly available tool can be used to enhance the researcher's ability to estimate chemical concentrations in wastewater treatment plant effluents, surface waters and in many drinking water outlets under mid and low flow conditions. The computer model covers over 240,000 river miles in the United States and includes 13,300 wastewater treatment plants and 1,700 municipal drinking water facilities downstream of the treatment plants (14, 15).

For the model to calculate the PEC, the user must include:
- the geographical extent to be assessed.
- the charge factor (per person usage rate - g/person/day).
- the removal of wastewater treatment.
- the decomposition rate in the river (k/day).
- the water flow (medium or low).

Wastewater treatment removal can be achieved through another exposure model called SimpleTreat. The safety assessment starts from the worst-case scenario, and later, if necessary, a more detailed analysis is done for validation.

Thus, even though it was not possible to study the high-level models in depth, the knowledge of the existence of each was of extreme importance for possible future partnerships.

iSTREEM® is a complete and ideal tool for an in-depth environmental safety assessment, should the need arise. That is, if the ingredient is of high environmental risk after the worst-case assessment performed with the screening tools, a more detailed assessment is possible via iSTREEM to understand the impact, considering different dilutions and different geographic locations.

 

Conclusion

These results of comparison of environmental modeling tools are unprecedented in the literature and provide the perspective information that can help in the development of safer cosmetics considering the recent exposure scenario.

With this study it was possible to perform detailed evaluation and comparison between environmental modeling screening tools.

The EUSES tool is an old system and is not easy to use, requiring many inputs for evaluation. The E-FAST tool, despite having the closest exposed population to Brazil, uses older (2003 date) and complex data such as effluent treatment removal for each substance. It is also not as complete as EUSES.

Finally, Chesar is a tool that facilitates data entry. It was considered the easiest tool to use and has clearer and more straightforward application steps. Among the screening tools, the Chesar tool was chosen for the initial assessment of ingredients that demonstrate potential environmental risk.

For the high-level environmental modeling tools, it was not possible to establish a comparison between the chosen models, as the models are private and have little data in the literature. Still, following the rational safety assessment, for a more detailed assessment after the first initial assessment via Chesar, iSTREEM can be used.

 

Author contributions

All the study was conducted by Caroline Inácio Bianchi and Patrícia Maria Berardo Gonçalves Maia Campos. Both researchers were responsible for the contextualization. Caroline was responsible for both the experimental and writing, while Patrícia was responsible for the supervision of the study and revision of the article.

 

Acknowledgements

The discussion of this work was supported by Natura&Co LATAM, who has great knowledge on the subject.

 

Conflicts of Interest

The Editor involved in the authorship of this manuscript had no participation in the review or decision process. Both authors have stated that there are no financial and/or personal relationships that could represent a potential conflict of interest.

 

References 
1.     Maia, J. I. B. (2017). Innovation in cosmetics-innovative makeup products: efficacy and safety. [Integrated Master’s Degree, University of Lisbon Faculty of Pharmacy]. University of Lisbon Repository. https://repositorio.ul.pt/bitstream/10451/36037/1/MICF_Joana_Maia.pdf
2.     Sheth J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die?. Journal of business research, 117, 280–283. https://doi.org/10.1016/j.jbusres.2020.05.059
3.     WHO (World Health Organization). Coronavirus disease (COVID-19) advice for the public. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public, accessed 28 June 2022.
4.     Loxton, M., Truskett, R., Scarf, B., Sindone, L., Baldry, G., & Zhao, Y. (2020). Consumer behaviour during crises: preliminary research on how coronavirus has manifested consumer panic buying, herd mentality, changing discretionary spending and the role of the media in influencing behavior. Journal of Risk and Financial Management, 13(8), 166. https://www.mdpi.com/1911-8074/13/8/166
5.     Duan, Y., Shang, B., Liang, W., Lin, Z., Hu, C., Baker, J. S., Wang, Y., & He, J. (2022). Predicting hand washing, mask wearing and social distancing behaviors among older adults during the covid-19 pandemic: an integrated social cognition model. BMC geriatrics, 22(1), 91. https://doi.org/10.1186/s12877-022-02785-2.
6.     Westbrook, G., & Angus, A. TOP 10 GLOBAL CONSUMER TRENDS 2021. Euromonitor International, 2021. Available at: https://go.euromonitor.com/white-paper-EC-2021-Top-10-Global-Consumer-Trends.html, accessed 18 April 2021.
7.     Mogelonsky, M. “A pandemia do Covid-19 chegou: Como os consumidores e as indústrias estão reagindo nos EUA?”. MINTEL. Available at: https://brasil.mintel.com/blog/a-pandemia-do-covid-19-chegou-como-os-consumidores-e-as-industrias-estao-reagindo-nos-eua, accessed 10 September 2020.
8.     Cadioli, G.F. & Campos, P. M. (2020). “Os Cosméticos em Tempos de Pandemia”. Cosmetics & Toiletries (Brasil), 32 (5), 40-41.
9.     SCCS members, & Other experts (2021). The SCCS Notes of Guidance for the testing of cosmetic ingredients and their safety evaluation, 11th revision, 30-31 March 2021, SCCS/1628/21. Regulatory toxicology and pharmacology : RTP, 127, 105052. https://doi.org/10.1016/j.yrtph.2021.105052
10.     ANVISA – Agência Nacional de Vigilância Sanitária. Guia para Avaliação de Segurança de Produtos Cosméticos, 2ª edition (2012). ANVISA. https://www.gov.br/anvisa/pt-br/centraisdeconteudo/publicacoes/cosmeticos/manuais-e-guias/guia-para-avaliacao-de-seguranca-de-produtos-cosmeticos.pdf
11.     Keller, V. D., Williams, R. J., Lofthouse, C., & Johnson, A. C. (2014). Worldwide estimation of river concentrations of any chemical originating from sewage-treatment plants using dilution factors. Environmental toxicology and chemistry, 33(2), 447–452. https://doi.org/10.1002/etc.2441
12.     ECHA. (2016) Guidance on Information Requirements and Chemical Safety Assessment, Chapter R. 16: Environmental exposure assessment.
13.     Grill, G., Li, J., Khan, U., Zhong, Y., Lehner, B., Nicell, J., & Ariwi, J. (2018). Estimating the eco-toxicological risk of estrogens in China's rivers using a high-resolution contaminant fate model. Water research, 145, 707–720. https://doi.org/10.1016/j.watres.2018.08.053
14.     Wang, X., Homer, M., Dyer, S. D., White-Hull, C., & Du, C. (2005). A river water quality model integrated with a web-based geographic information system. Journal of environmental management, 75(3), 219–228. https://doi.org/10.1016/j.jenvman.2004.11.025
15.     Kapo, K. E., DeLeo, P. C., Vamshi, R., Holmes, C. M., Ferrer, D., Dyer, S. D., Wang, X., & White-Hull, C. (2016). iSTREEM(®) : An approach for broad-scale in-stream exposure assessment of "down-the-drain" chemicals. Integrated environmental assessment and management, 12(4), 782–792. https://doi.org/10.1002/ieam.1793